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Eur J Cardiothorac Surg 2004;25:884-889
© 2004 Elsevier Science NL

A model for the internal evaluation of the quality of care after lung resection in the elderly

Unit of Thoracic Surgery, Department of Respiratory Diseases, "Umberto I°" Regional Hospital, Ancona, Italy

Received 14 November 2003; received in revised form 28 January 2004; accepted 29 January 2004.

^* Corresponding author. Address: Via S. Margherita 23, Ancona 60129, Italy. Tel.: +39-071-59-644-39; fax: +39-071-596-4433
e-mail: alexit_2000{at}yahoo.com

Objectives: The objective of this study was to develop a logistic model for internal audit in a population of elderly patients submitted to lung resection. Methods: Three hundred twenty-six patients older than 70 years of age and submitted to lung resection for lung carcinoma were retrospectively analyzed. Univariate and logistic regression analyses yielded a model for the prediction of postoperative complications that was validated by bootstrap resampling analysis. The model was then used to assess the performance of our unit during two successive periods of activity (‘early’, 1993–1999; ‘late’, 2000–2003). Results: Significant independent predictors of postoperative complications were a low ppoFEV1 (P<0.0001), the presence of concomitant cardiac disease (P=0.01) and extended resection (P=0.03). The observed morbidity rate in the late period was higher than that in the early period (48.3 vs. 33.8%; P=0.008). The predicted morbidity rate was also higher in the late period, compared to that in the early period (44 vs. 39%; P=0.003). Moreover, no differences were noted between predicted and observed morbidity rates in each of the two periods (early, P=0.4; late, P=0.5). Conclusions: We showed that applying a model of risk-adjustment in elderly patients submitted to lung resection was useful for the internal evaluation of the quality of care and prevented misleading information derived by the comparison of the crude rates of the observed morbidity.

Key Words: Postoperative complications • Lung resection • Lung cancer • Audit • Quality of care

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